Our goal is to evolve the field of biosimulation, and to catalyze biological research wherever biosimulation modeling is used. Our focus is on the rapid development of multi-scale models that leverage prior model development-that is, to facilitate knowledge sharing and reuse. Our novel approach to improving knowledge sharing is to use semantic annotation based on a common foundation: the basic laws of physical dynamics that govern all biological processes. With this common foundation, and with annotations against the common physical semantics, we can automatically detect and make semantic connections between biosimulation models. These connections are a key step to allow researchers to reuse and recombine models in new ways. Annotation can be a bottleneck in this workflow, and our proposal aims to both address this bottle- neck via an automatic annotation process, and then to demonstrate that this semantic annotation of models is sufficient for researchers to more easily find, understand, and reuse models to more rapidly produce new, merged models. We will demonstrate these results both in a controlled, laboratory set- ting, and in the wild, in collaboration with researchers who are pat of the Virtual Physiological Rat Project (VPR). More specifically, we will (aim 1) develop new methods for automatically assigning semantic annotations to biosimulation models. At the end of this aim, we will have a large corpus of annotated models to evaluate and extend in the next two aims. Next (aim 2), in a controlled, laboratory setting, we will test both the efficiency (how fast can an integrated model be built) an efficacy (how accurate is the resulting model) of our methods. Finally, in aim 3, we will collaborate closely with the VPR scientists to achieve two ends. First, we must validate that our methods are useful in the real world of biosimulation model development. Second, we will leverage the VPR project to participate in and then lead workshops around our methods and ideas of semantic annotation for models. These workshops should lead to additional use-cases and users for further validation, and also for opportunities to promulgate our methods and broaden the long-term impact of our work.